Updated 24 October 2026
Influence operations, as platforms and researchers have documented them
What coordinated inauthentic behaviour is, how fake networks are detected and attributed, which tactics recur, and what each takedown report says, with every attribution credited.
What influence operations are
- AI-generated personas in influence operations
What Meta, OpenAI and the EEAS have reported about AI-made profile photos, fake newsreaders and AI-written text in influence networks, with dates.
- Fake news websites in influence operations
Spoofed outlets, invented news brands and aggregator networks as documented by Meta, Microsoft, OpenAI, Google and the EEAS, with dates and counts.
- Influence operation tactics documented in official reports
Fake personas, fake media brands, paid ads, self-amplification and AI-written content, as Meta, Google, OpenAI and the EEAS have documented them.
- What coordinated inauthentic behaviour means
How Meta defines coordinated inauthentic behaviour, how X, TikTok, Bluesky and Microsoft word similar rules, and what Meta has reported since 2017.
How they are detected
- How attribution of influence operations works
How Meta, Google, OpenAI, Microsoft, X and the EEAS word attribution, from country of origin to named entities, and what terms like likely and linked mean.
- How platforms detect fake networks
What Meta, OpenAI, TikTok and Google say about finding influence networks: expert investigations, automated detection, behavioural signals and shared tips.
- How to read a takedown report
What the counts, follower figures, ad spend, origin labels, impact scores and threat indicators in Meta, OpenAI, Google and EEAS reports mean.
Reported networks
- Commercial influence for hire in official takedown reports
How Meta, OpenAI, Google and the EU have reported marketing and PR firms behind covert influence networks, with firm names as each report gives them.
- Google TAG bulletins explained
How Google Threat Analysis Group bulletins list terminated YouTube channels, blogs, ads accounts and blocked domains, with 2025 examples.
- Influence operations targeting Africa
Networks targeting African audiences as reported by Meta, OpenAI, Google, the EEAS and the Africa Center for Strategic Studies, with origins as attributed.
- Influence operations targeting elections
Election-related networks reported by Meta, OpenAI, Google, Microsoft and the EEAS from 2023 to 2025, with origins as each body attributed them.
- Meta's adversarial threat reports explained
What Meta's adversarial threat reports contain, how each network entry is laid out, and what the Q4 2024, Q1 2025 and Q2/Q3 2025 reports listed.
- OpenAI threat reports explained
What OpenAI's reports on disrupting malicious uses of AI contain, how cases are rated on the Breakout Scale, and what the 2024 to 2026 reports found.
Rules and research
- EU reports on foreign information manipulation and interference
What the EEAS reports on foreign information manipulation and interference count, the periods they cover, and how they classify channels.
- Research datasets on influence operations
Public datasets and archives on influence operations from Meta, Google, OpenAI, the EEAS, Princeton and Oxford, with what each covers and its period.
- The X and Twitter information operations archive
What Twitter's archive of state-backed information operations held, how the X Moderation Research Consortium shares data, and what changed in 2022.